Objective: To assess the accuracy of data linkage across the spectrum of emergency
care in the absence of a unique patient identifier, and to use the linked data to examine
service delivery outcomes in an emergency department (ED) setting.
Design: Automated data linkage and manual data linkage were compared to
determine their relative accuracy. Data were extracted from three separate health
information systems: ambulance, ED and hospital inpatients, then linked to provide
information about the emergency journey of each patient. The linking was done
manually through physical review of records and automatically using a data linking tool
(Health Data Integration) developed by the CSIRO (Commonwealth Scientific and
Industrial Research Organisation). Match rate and quality of the linking were compared.
Setting: 10 835 patient presentations to a large, regional teaching hospital ED over a
2-month period (August – September 2007).
Results: Comparison of the manual and automated linkage outcomes for each pair of
linked datasets demonstrated a sensitivity of between 95% and 99%; a specificity of
between 75% and 99%; and a positive predictive value of between 88% and 95%.
Conclusions: Our results indicate that automated linking provides a sound basis for
health service analysis, even in the absence of a unique patient identifier. The use of an
automated linking tool yields accurate data suitable for planning and service delivery
purposes and enables the data to be linked regularly to examine service delivery
outcomes.